Unclear consumption
Teams don’t always know which tasks and loops are driving costs.
Problem 04 · Token costs
More AI. More tokens. But where is the cost control?
More agents and iterations drive up consumption. Without transparency and clean specifications, you get avoidable loops and token costs that are hard to plan.
BeeHive combines more efficient workflows with insight into AI consumption.
Without BeeHive
- Prompt loop
- Agent run ?
- Regeneration
- Rework
- Model X
- Cost ?
Token consumption without an overview.
With BeeHive
- Spec check
- Effort
- Build
- Usage analysis
Consumption visible in BeeHive Insights.
The problem
What happens without a shared process
The challenge isn’t AI itself – it’s the lack of structure, control and traceability in day-to-day development.
Unnecessary iterations
Imprecise requirements trigger repeated generation and rework.
No shared control
Without an overview, workflows are hard to compare and improve.
More AI. More tokens. But where is the cost control?
The solution · BeeHive
BeeHive combines more efficient workflows with insight into AI consumption.
BeeHive connects AI agents, standardized commands, project knowledge and verifiable work steps in one coordinated software engineering process.
- Check specifications earlierSpot ambiguities before expensive build loops start.
- Orchestrate agents with purposeStructure tasks, context and execution along defined workflows.
- Make consumption visibleBring usage and cost information together in Insights.
- Optimize continuouslyUse results and consumption as the basis for process improvements.
How BeeHive addresses this challenge
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Validate specifications before the build
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Estimate effort and token demand early
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Run agents deliberately, not unchecked
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Analyze consumption and optimization potential
BeeHive · Usage
Making AI costs traceable.
The cockpit shows which feature and which agent generates how much usage – relative to a budget you set yourself.
- Usage per feature, agent and model
- Budget line per sprint or project
- A basis for model and routing decisions
BeeHive Token usage · sprint 14
FeatureAgentModelFEAT-042DATEV export1.8 MFEAT-040Client dashboard1.1 MFEAT-045Partner portal SSO0.6 MFEAT-039Payment reminders0.4 MBackendTestsReview
Show me this sprint’s token usage by feature and agent.
BeeHive
How does this work with your team and repository?
We’ll show you BeeHive using a realistic development scenario.
More challenges
What else is slowing down your AI development?
Discover more typical challenges – and how BeeHive addresses them.
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Problem 01
AI code becomes hard to maintain.
Secure code quality and maintainability.
Discover the solution -
Problem 02
Every developer uses LLMs differently.
Create consistent processes.
Discover the solution -
Problem 03
Code is written faster than documentation.
Automate traceability.
Discover the solution -
Problem 05
Nobody has an overview of AI usage.
See privacy, compliance and security KPIs in one place.
Discover the solution -
Problem 06
Unclear specifications create rework.
Validate requirements before implementation.
Discover the solution
FAQ
Frequently asked questions about token costs
Can BeeHive work with existing model access?
Connecting your existing model access is part of the integration approach and is assessed technically for each provider.
Experience BeeHive live
Build faster. With standards, insight and control.
See how BeeHive integrates AI-assisted development into one coordinated process.